{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Kats 202 - Detection with Kats\n",
    "\n",
    "This tutorial will introduce detection in Kats, including change point detection, outlier detection, and trend detection.  It is a more detailed and in-depth introduction than the one provided in Kats 101.  The table of contents for Kats 202 is as follows:\n",
    "\n",
    "1. Changepoint Detection      \n",
    "    1.1 CUSUMDetector      \n",
    "    1.2 BOCPDetector      \n",
    "    1.3 RobustStatDetector      \n",
    "2. Outlier Detection      \n",
    "    2.1 OutlierDetector      \n",
    "    2.2 MultivariateAnomalyDetector      \n",
    "3. Trend Detection      \n",
    "    3.1 MKDetector       \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** We provide two types of tutorial notebooks\n",
    "- **Kats 101**, basic data structure and functionalities in Kats (this tutorial)  \n",
    "- **Kats 20x**, advanced topics, including advanced forecasting techniques, advanced detection algorithms, `TsFeatures`, meta-learning, etc. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture\n",
    "# For Google Colab:\n",
    "!pip install kats\n",
    "!wget https://raw.githubusercontent.com/facebookresearch/Kats/main/kats/data/air_passengers.csv\n",
    "!wget https://raw.githubusercontent.com/facebookresearch/Kats/main/kats/data/multivariate_anomaly_simulated_data.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jeffhandl/kats_venv/lib/python3.7/site-packages/ipykernel_launcher.py:5: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses\n",
      "  \"\"\"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<module 'logging' from '/opt/homebrew/Cellar/python37/3.7.5_3/Frameworks/Python.framework/Versions/3.7/lib/python3.7/logging/__init__.py'>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import logging\n",
    "from imp import reload\n",
    "from datetime import datetime, timedelta\n",
    "import sys\n",
    "sys.path.append(\"../\")\n",
    "\n",
    "from kats.consts import TimeSeriesData\n",
    "reload(logging)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Changepoint Detection <a class=\"anchor\" id=\"kats_basics\"></a>\n",
    "\n",
    "Changepoint detection tries to identify times when the probability distribution of a stochastic process or time series changes, e.g. the change of mean in a time series. It is one of the most popular detection tasks in time series analysis. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **1.1 `CUSUMDetector`**\n",
    "\n",
    "\n",
    "CUSUM is a method to detect an up/down shift of means in a time series. Our implementation has two main steps:\n",
    "\n",
    "\n",
    "1. **Locate the change point:** This is an iterative process where we initialize a change point (in the middle of the time series) and CUSUM time series based on this change point. The next changepoint is the location where the previous CUSUM time series is maximized (or minimized). This iteration continues until either 1) a stable changepoint is found or 2) we exceed the limit number of iterations.\n",
    "2. **Test the change point for statistical significance:** Conduct log likelihood ratio test to test if the mean of the time series changes at the changepoint calculated in Step 1. The null hypothesis is that there is no change in mean.\n",
    "\n",
    "By default, we report a detected changepoint if and only if we reject the null hypothesis in Step 2.  If we want to see all the changepoints, we can use the `return_all_changepoints` parameter in `CUSUMDetector` and set it to `True`.\n",
    "\n",
    "Here are a few additional points worth mentioning:\n",
    "\n",
    "* We assume there is at most one increase change point and at most one decrease change point. You can use the `change_directions` argument in the detector to specify whether you are looking an increase, a decrease, or both (default is both).\n",
    "* We use Gaussian distribution as the underlying model to calculate the CUSUM time series value and conduct the hypothesis test.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The full set of parameters for the `detector` method in `CUSUMDetector`, all of which are optional and have default values, are as follows: \n",
    "* **threshold**: float, significance level;\n",
    "* **max_iter**: int, maximum iteration in finding the changepoint;\n",
    "* **delta_std_ratio**: float, the mean delta has to be larger than this parameter times std of the data to be considered as a change;\n",
    "* **min_abs_change**: int, minimal absolute delta between mu0 and mu1\n",
    "* **start_point**: int, the start idx of the changepoint, None means the middle of the time series;\n",
    "* **change_directions**: list\\[str], a list contain either or both 'increase' and 'decrease' to specify what type of change to be detected;\n",
    "* **interest_window**: list\\[int, int], a list containing the start and end of the interest window where we will look for a change point. Note that the llr will still be calculated using all data points;\n",
    "* **magnitude_quantile**: float, the quantile for magnitude comparison, if none, will skip the magnitude comparison;\n",
    "* **magnitude_ratio**: float, comparable ratio;\n",
    "* **magnitude_comparable_day**: float, maximal percentage of days can have comparable magnitude to be considered as regression;\n",
    "* **return_all_changepoints**: bool, return all the changepoints found, even the insignificant ones."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Review Basic Usage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We begin by reviewing the basic usage of `CUSUMDetector` from the Kats 101 tutorial.  This simple example is the same one we first introduced there."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import packages\n",
    "from kats.detectors.cusum_detection import CUSUMDetector\n",
    "\n",
    "# synthesize data with simulation\n",
    "np.random.seed(10)\n",
    "df_increase_decrease = pd.DataFrame(\n",
    "    {\n",
    "        'time': pd.date_range('2019-01-01', periods=60),\n",
    "        'increase':np.concatenate([np.random.normal(1,0.2,30), np.random.normal(2,0.2,30)]),\n",
    "        'decrease':np.concatenate([np.random.normal(1,0.3,50), np.random.normal(0.5,0.3,10)]),\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsd = TimeSeriesData(df_increase_decrease.loc[:,['time','increase']])\n",
    "detector = CUSUMDetector(tsd)\n",
    "change_points = detector.detector(change_directions=[\"increase\"])\n",
    "\n",
    "detector.plot(change_points)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsd = TimeSeriesData(df_increase_decrease.loc[:,['time','decrease']])\n",
    "detector = CUSUMDetector(tsd)\n",
    "change_points = detector.detector(change_directions=[\"decrease\"])\n",
    "\n",
    "detector.plot(change_points)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interpret the result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we do not specify which change directions we are looking for using the `change_directions` parameter, `CUSUMDetector` will look for both increases and decreases. In the case below where there is only an increase, it will detect that increase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsd = TimeSeriesData(df_increase_decrease.loc[:,['time','increase']])\n",
    "detector = CUSUMDetector(tsd)\n",
    "change_points = detector.detector()\n",
    "\n",
    "detector.plot(change_points)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look at how we can interpret the results of the `CUSUMDetector`.  The return type of the `detector` method is `List[CUSUMChangePoint]`. Most `detector` methods in Kats return this same structure, but some use a subclass of `TimeSeriesChangePoint` with additional information specific to that detector."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CUSUMChangePoint(start_time: 2019-01-30 00:00:00, end_time: 2019-01-30 00:00:00, confidence: 1.0, direction: increase, index: 29, delta: 0.9837320835853411, regression_detected: True, stable_changepoint: True, mu0: 1.0395982783530555, mu1: 2.0233303619383967, llr: 128.93223399207324, llr_int: inf, p_value: 0.0, p_value_int: nan)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the change point, since we only detected one change point \n",
    "# We can access it with change_points[0] because we only found one change point above\n",
    "change_point = change_points[0]\n",
    "change_point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's look at the additional attributes of `CUSUMChangePoint` beyond those of `TimeSeriesChangePoint`:\n",
    "* **direction**: str, the change point direction, either 'increase' or 'decrease';\n",
    "* **cp_index**: int, the index of the change point;\n",
    "* **mu0**: float, mean before the change point;\n",
    "* **mu1**: float, mean after the change point;\n",
    "* **delta**: float, mu1 - mu0;\n",
    "* **llr_int**: float, the log likelihood ratio in interest window, or `inf` if not using an interet window;\n",
    "* **llr**: float, the log likelihood ratio for the full time series;\n",
    "* **regression_detected**: bool, is the change point detected by the algorithm (only relevant when `return_all_changepoints=True`);\n",
    "* **stable_changepoint**: bool, indicates whether the algorithm converged to this point (rather than hitting the iteration limit);\n",
    "* **p_value**: float, p-value for the likelihood ratio test;\n",
    "* **p_value_int**: float, p-value for the likelihood ratio test in interest_window, or `nan` if not using an interest window."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will explain interest windows in the next section, but for now, notice that since we are not using the `interet_window` parameter in `CUSUMDetector`, the metadata values of `llr_int` and `p_value_int` are `inf` and `nan` respectively.  These values will be populated properly only when we use the `interet_window` parameter in `CUSUMDetector`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Introducing Interest Windows\n",
    "\n",
    "Sometimes we want to look for a changepoint in a specific window, which we call an interest window and can be specified using the `interest_window` paramter in `CUSUMDetector`.  Here is what the detector essentially does when using an interest window:\n",
    "\n",
    "1. Do both of the major aforementioned steps of CUSUM (locate the change point and test for signifiance) when only considering the data within the `interest_window`.  By default, continue only if we find a changepoint and reject the null hypothesis.\n",
    "2. Do an additional test for statistical significance on the changepoint found in step 1 using the entire input time series (not just the restriction to `interest_window`).  By default, return this changepoint only if we reject the null hypothesis (unless we set the parameter `return_all_changepoints` to `True`).\n",
    "\n",
    "Since the `CUSUMDetector` can only return one change point in each direction, we can use the `interest_window` parameter narrow the search window in the case that the input time series contains multiple change points.  However, the change point point we return must pass the likelihood ratio test for the entire time series (step 2 above) in addition to passing the likelihood ratio test within the interest window (step 1 above)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's return to the first example where we used `CUSUMDetector` to detect an increase.  If we set the `interest_window` to a window that contains the change point that we found above, we will find it again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# limit the interest_window between 20th and 40th data point\n",
    "tsd = TimeSeriesData(df_increase_decrease.loc[:,['time','increase']])\n",
    "detector = CUSUMDetector(tsd)\n",
    "change_points = detector.detector(interest_window=[20,40])\n",
    "\n",
    "detector.plot(change_points)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we set the `interest_window` to a window that does not find any change point, we will return no change point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:No change points detected!\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# limit the interest_window to last 20 the datapoint and no change point detected\n",
    "tsd = TimeSeriesData(df_increase_decrease.loc[:,['time','increase']])\n",
    "detector = CUSUMDetector(tsd)\n",
    "change_points = detector.detector(interest_window=[40,60])\n",
    "\n",
    "detector.plot(change_points)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Daily Seasonality with Interest Windows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we are using an interest window in a time series with seasonality, we can get a false positive.  Here we show how this happens and how we can address the problem.  Let's start by generating a time series with seasonality.  We use a method from our test functions in `CUSUMDetectorTest` to simulate the data or this problem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from kats.tests.detectors.test_cusum_detection import CUSUMDetectorTest\n",
    "\n",
    "# Here's where we load the seasonal data\n",
    "np.random.seed(1)\n",
    "periodicity=24\n",
    "total_cycles=3\n",
    "seasonal_term = CUSUMDetectorTest.simulate_seasonal_term(\n",
    "    periodicity=periodicity, total_cycles=total_cycles, noise_std=3, harmonics=2\n",
    ")\n",
    "seasonal_term = seasonal_term / seasonal_term.std() * 2\n",
    "residual = np.random.normal(0, 1, periodicity * total_cycles)\n",
    "data = seasonal_term + residual\n",
    "data -= np.min(data)\n",
    "\n",
    "# Load the data into a DataFrame and a TimeSeriesData\n",
    "df_seasonality = pd.DataFrame(\n",
    "    {\n",
    "        \"time\": pd.date_range(\n",
    "            \"2020-01-01\", periods=periodicity * total_cycles, freq=\"H\"\n",
    "        ),\n",
    "        \"seasonality\": data,\n",
    "    }\n",
    ")\n",
    "ts_seasonality = TimeSeriesData(df_seasonality)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we do detection using the interest window below, we get a false positive.  It is clear that the change point detected below is not a changepoint with respect to an entire series.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "detector = CUSUMDetector(ts_seasonality)\n",
    "\n",
    "# Without magnitude comparison\n",
    "change_points = detector.detector(\n",
    "    interest_window=[\n",
    "        periodicity * (total_cycles - 1),\n",
    "        periodicity * total_cycles - 1,\n",
    "    ],\n",
    "    change_directions=[\"increase\"],\n",
    ")\n",
    "\n",
    "detector.plot(change_points)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can mitigate false positives here by comparing the magnitude of the time series in the interest window to compare the magnitude of the time series in the interest window to the magnitude of the the time series prior to the interest window.  We need three additional parameters to do this: `magnitude_quantile`, `magnitude_comparable_day`, and `magnitude_ratio`.\n",
    "\n",
    "Here is the procedure for using these parameters to restrict the number of false positives when detecting an increase (when looking for decreases, the time series values are multipled by -1 prior to using this procedure):\n",
    "\n",
    "1) Calculate the `magnitude_quantile` percentile of the timeseries within the `interest_window`.  Call this value `p`    \n",
    "2) Calculate the `magnitude_quantile` percentile over a sliding window of length equal to the length of `interest_window` in the time series prior to `interest_window`.  Count the proportion of intervals for which this percentile is smaller than `p / magnitude_ratio`.  Include this changepoint if and only if this proportion of days exceeds `magnitude_comparable_day`.\n",
    "\n",
    "The values of `magnitude_comparable_day` and `magnitude_ratio` are 0.5 and 1.3 by default, and we only include them below for readability.    When the `magnitude_quantile` is not included as a paramter, we are not doing a magnitude ratio comparison.  Below we have `magnitude_quantile =1` which means the value of `p` in step 1 above is equal to the maximium value of the time series over the `interest_window`.  Then based on the parameters we are using, we will keep a changepoint detected in `interest_window` only if at least half of the intervals prior to `interest_window` with the same length as `interest_window` have a maximum value not exceeding `p/1.3`.\n",
    "\n",
    "As we see below, adding this additional restriction on the change points we detect removes the false positive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:No change points detected!\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "detector = CUSUMDetector(ts_seasonality)\n",
    "\n",
    "\n",
    "# With magnitude comparison, seasonal false positive not detected\n",
    "change_points = detector.detector(\n",
    "    interest_window=[\n",
    "        periodicity * (total_cycles - 1),\n",
    "        periodicity * total_cycles - 1,\n",
    "    ],\n",
    "    magnitude_quantile=1, # enable magnitude comparison\n",
    "    magnitude_comparable_day=0.5, # this is the default value\n",
    "    magnitude_ratio=1.3, # this is the default value\n",
    "    change_directions=[\"increase\"],\n",
    ")\n",
    "\n",
    "detector.plot(change_points)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Detecting Multiple Change Points with Interest Windows\n",
    "In most use cases, there are more than one change point, and you might want to monitor the regressions continuously. Here shows how can we achieve detecting multiple change points over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# synthesize data with simulation\n",
    "np.random.seed(10)\n",
    "df_multi_cps = pd.DataFrame(\n",
    "    {\n",
    "        'time': pd.date_range('2019-01-01', periods=100),\n",
    "        'y':np.concatenate([\n",
    "            np.random.normal(1, 0.2, 30), \n",
    "            np.random.normal(2, 0.2, 30),\n",
    "            np.random.normal(0, 0.2, 20),\n",
    "            np.random.normal(3, 1, 20),\n",
    "        ]),\n",
    "    }\n",
    ")\n",
    "multi_cp_ts = TimeSeriesData(df_multi_cps)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Iterate through the time series using a sliding window, and partition each sliding window into a historical window and a scan window.  The length of each sliding window then will be `historical_window + scan_window`, where `historical_window` and `scan_window` are chosen suitably for the time series being considered.  Run `CUSUMDetector` on the sliding window with the scan window as the interest window.  Repeat and collect all changepoints until the sliding window reaches the end of the time series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "historical_window = 20\n",
    "scan_window = 10\n",
    "step = 5\n",
    "changepoints = []\n",
    "n = len(df_multi_cps)\n",
    "for end_idx in range(historical_window + scan_window, n, step):\n",
    "    tsd = multi_cp_ts[end_idx - (historical_window + scan_window) : end_idx]\n",
    "    changepoints += CUSUMDetector(tsd).detector(interest_window=[historical_window, historical_window + scan_window])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can plot the results.  To use the `plot` method in `CUSUMDetector`, we need to initiate a new `CUSUMDetector` over the entire `multi_cp_ts` and call the `detector` method, but actually using this new detector for anything."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the results\n",
    "detector = CUSUMDetector(multi_cp_ts) # we are not really using this detector\n",
    "detector.detector() # this call to detector is not being used for anything\n",
    "\n",
    "detector.plot(changepoints)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **1.2 BOCPDetector**\n",
    "\n",
    "Bayesian Online Change Point Detection (BOCPD) is a method for detecting sudden changes in a time series that persist over time. Our implementation is faithful to [\"Bayesian Online Changepoint Detection\"](https://arxiv.org/abs/0710.3742) (Adams & McKay, 2007).  There are a coupple properties that distinguish BOCPD from the other change point detection methods supported in Kats:\n",
    "\n",
    "* **Online Model:** This detection does not need to know the entire series apriori.  It only need to look a few steps ahead (specified by the `lag` parameter in the `detector` method) to make predictions, and it revises its predictions as new data arrives.  \n",
    "* **Bayesian Model:** The user can specify prior beliefs about the probability of a changepoint (using the `changepoint_prior` paremeter in the `detector` method) and specify the the parameters of the underlying probability model that generates the time series (using the `model_parameters` parameter in the `detector` method).  Right now we support 3 diferent types of underlying probability models (specified using the `model` parameter in the `detector` method).\n",
    "\n",
    "The basic idea of this detection method is uses Bayesian inference to decide if the next point is improbable.  This requires the user to specify (or use default values for) the **probability of a change point** and **underlying predictive model (UPM)** that generates the incoming data points in the time series.  Currently we support three different types of underlying models:\n",
    "1. Normal Distribution (unknown mean, known variance)    \n",
    "2. Trend Change Distribution    \n",
    "3. Poisson Process Model    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The full set of parameters for the `detector` method in `BOCPDetector`, all of which are optional and have default values, are as follows: \n",
    "\n",
    "* **model**: This specifies the underlying probabilistic model (UPM) that generates the data within each segment.  Currently, allowed models are:\n",
    "    * NORMAL_KNOWN_MODEL: Normal model with variance known. Use this to find level shifts in normally distributed data.\n",
    "    * TREND_CHANGE_MODEL : This model assumes each segment is generated from ordinary linear regression. Use this model to understand changes in slope, or trend in time series.\n",
    "    * POISSON_PROCESS_MODEL: This assumes a Poisson generative model. Use this for count data, where most of the values are close to zero.\n",
    "\n",
    "* **model_parameters**: Model Parameters correspond to specific parameters for a specific model. They are defined in the NormalKnownParameters, TrendChangeParameters, PoissonModelParameters classes.\n",
    "\n",
    "* **lag**: integer referring to the lag in reporting the changepoint. We report the changepoint after seeing \"lag\" number of data points. Higher lag gives greater certainty that this is indeed a changepoint. Lower lag will detect the changepoint faster. This is the trade-off.\n",
    "\n",
    "* **changepoint_prior**: This is a Bayesian algorithm. Hence, this parameter specifies the prior belief on the probability that a given point is a changepoint. For example, if you believe 10% of your data will be a changepoint, you can set this to 0.1.\n",
    "\n",
    "* **threshold**: We report the probability of observing the changepoint at each instant. The actual changepoints are obtained by denoting the points above this threshold to be a changepoint.\n",
    "\n",
    "* **debug**: This surfaces additional information, such as the plots of predicted means and variances, which allows the user to see debug why changepoints were not properly detected."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** When using the normal distribution for a UPM, there are two ways to pick the prior parameters:      \n",
    "* Use an empirical prior and estimate the parameters from the data (set attribute `empirical=True` in `NormalKnownParameters`)           \n",
    "* Specify the mean and precision of the distribution "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basic Usage\n",
    "Here we show the basic usage of `BOCPDetector` to detect mean shift."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We begin by simulating some data with some change points using the `Simulator` class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kats.utils.simulator import Simulator\n",
    "\n",
    "sim = Simulator(n=450, start='2020-01-01', freq='H')\n",
    "ts_bocpd = sim.level_shift_sim(noise=0.05, seasonal_period=1)\n",
    "\n",
    "# plot the simulated data\n",
    "ts_bocpd.plot(cols=['value'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we run BOCPD to find the change points in this simulated time series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jeffhandl/kats_venv/lib/python3.7/site-packages/ax/core/parameter.py:468: UserWarning:\n",
      "\n",
      "`sort_values` is not specified for `ChoiceParameter` \"known_prec_multiplier\". Defaulting to `True` for parameters of `ParameterType` FLOAT. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
      "\n",
      "/Users/jeffhandl/kats_venv/lib/python3.7/site-packages/ax/core/parameter.py:468: UserWarning:\n",
      "\n",
      "`sort_values` is not specified for `ChoiceParameter` \"cp_prior\". Defaulting to `True` for parameters of `ParameterType` FLOAT. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kats.detectors.bocpd import BOCPDetector, BOCPDModelType, TrendChangeParameters\n",
    "\n",
    "# Initialize the detector\n",
    "detector = BOCPDetector(ts_bocpd)\n",
    "\n",
    "\n",
    "changepoints = detector.detector(\n",
    "    model=BOCPDModelType.NORMAL_KNOWN_MODEL # this is the default choice\n",
    ")\n",
    "\n",
    "# Plot the data\n",
    "detector.plot(changepoints)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interpret the results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The return type of the `detector` method is `List[BOCPDChangePoint]`.  Let's see what that looks like for one of the change points detected above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BOCPDChangePoint(start_time: 2020-01-05T03:00:00.000000000, end_time: 2020-01-05T03:00:00.000000000, confidence: 0.9752663452994146, model: BOCPDModelType.NORMAL_KNOWN_MODEL, ts_name: value)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp = changepoints[0]\n",
    "cp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The additional attributes of `BOCPDChangePoint` beyond those of `TimeSeriesChangePoint` are:\n",
    "* **detector_type:** This will always be `kats.detectors.bocpd.BOCPDetector`\n",
    "* **model:** The type of the underlying predictive model, either `NORMAL_KNOWN_MODEL`, `TREND_CHANGE_MODEL`, or `POISSON_PROCESS_MODEL`\n",
    "* **ts_name**: the name of the time series\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **1.3 RobustStatDetector**\n",
    "\n",
    "`RobustStatDetector`, like `CUSUMDetector`, is a change point detection algorithms that finds mean shifts.  It works as follows:\n",
    "1. Smooth the time series using a moving average\n",
    "2. Calculate the differences in the smoothed time series over a fixed number of points (specified by the `comparison_window` parameter in the `detector` method).\n",
    "3. Calculate the z-scores and p-values for the differences calculated in step 2.  Return points where the p-value is smaller than a prescribed threshold (specified by the `p_value_cutoff` parameter in the dtector method`)\n",
    "\n",
    "Unlike `CUSUMDetector`, `RobustStatDetector` can detect multiple change points in a single run.  After a basic example, we will show an example with multiple change points."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The full set of parameters for the `detector` method in `RobustStatDetector`, all of which are optional and have default values, are as follows: \n",
    "* **p_value_cutoff**: float, the p-value threshold to flag the change point; \n",
    "* **smoothing_window_size**: int, the length of the smoothing window;\n",
    "* **comparison_window**: int, the step of the diff function, i.e. how many data points you want the algorithm look back to make the comparison."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basic Usage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We start by showing how to use `RobustStatDetector` using the same example we initially provided for `CUSUMDetector`.  The usage is straightforward."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import package\n",
    "from kats.detectors.robust_stat_detection import RobustStatDetector\n",
    "\n",
    "tsd = TimeSeriesData(df_increase_decrease.loc[:,['time','increase']])\n",
    "detector = RobustStatDetector(tsd)\n",
    "change_points = detector.detector()\n",
    "\n",
    "detector.plot(change_points)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The return type of the `detector` method is `List[RobustStatChangePoint]`.  Let's see what that looks like the change point detected above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TimeSeriesChangePoint(start_time: 2019-01-31T00:00:00.000000000, end_time: 2019-01-31T00:00:00.000000000, confidence: 0.9932728251020368)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "change_point = change_points[0]\n",
    "change_point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The attributes of `RobustStatChangePoint` beyond those of `TimeSeriesChangePoint` are:\n",
    "* **metric:** The raw value of the metric at the time of the change point  \n",
    "* **index:** The index of the change point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multiple Changepoints\n",
    "The `RobustStatDetector` can detect multiple change points in one time series by one run. One caution here is that the algorithm will use the full time series to compute the z-score, which means it might impact which change points are detected, e.g. it might not be able to detect a smaller change when there is a bigger change in the time series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ts_bocpd = TimeSeriesData(ts_bocpd.to_dataframe())\n",
    "detector = RobustStatDetector(ts_bocpd)\n",
    "changepoints = detector.detector(p_value_cutoff = 5e-3, comparison_window=2)\n",
    "\n",
    "# plot the results\n",
    "detector.plot(changepoints)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsd = TimeSeriesData(df_multi_cps)\n",
    "detector = RobustStatDetector(tsd)\n",
    "# even setting the p_value to be 0.1 it cannot detect the first change point, while there are already many FPs in the results\n",
    "changepoints = detector.detector(p_value_cutoff = 1e-1, comparison_window=2)\n",
    "\n",
    "detector.plot(changepoints)\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To avoid this we can again use the same way in `CUSUMDetector` to detect multiple change points by cutting the long time sereis into several different shorter sections."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Outlier Detection\n",
    "Outliers in Time Series can cause a lot of issues in downstream processing. Therefore, removing outliers is important in any time series analysis. In Kats, we have three algorithms detecting outliers, one for univariate time series, one for multi-variate time series and one for detecting irregular daily patterns."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **2.1 OutlierDetector**\n",
    "We provide the `OutlierDetector` module to detect outliers in time series. Since outliers can cause so many problems in downstream processing, it is important to be able to detect them. `OutlierDetector` also provides functionality to handle or remove outliers once they are found.\n",
    "\n",
    "Our outlier detection algorithm works as follows:\n",
    "* We do a [seasonal decomposition](https://www.statsmodels.org/stable/generated/statsmodels.tsa.seasonal.seasonal_decompose.html) of the input time series, with additive or multiplicative decomposition as specified (default is additive)\n",
    "* We generate a residual time series by either removing only trend or both trend and seasonality if the seasonality is strong.\n",
    "* We detect points in the residual which are outside 3 times the inter quartile range. This multiplier can be tuned using the `iqr_mult` parameter in `OutlierDetector`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the parameters when initializing `OutlierDetector`:\n",
    "* **data**: `TimeSeriesData` object with the time series\n",
    "* **decomp**: `additive` or 'multiplicative' (default is additive)\n",
    "* **iqr_mult**: `float`, multiplier on inter quartile range is used to classify outliers (default is 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we recap the example from the Kats 101 Tutorial of how to use `OutlierDetector` with the `air_passengers` data set.  Our example manually inserts outliers into the `air_passengers` data set and uses `OutlierDetector` to find them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load the air_passenger data set\n",
    "try: # If running on Jupyter\n",
    "    air_passengers_outlier_df = pd.read_csv(\"../kats/data/air_passengers.csv\")\n",
    "except FileNotFoundError: # If running on colab\n",
    "    air_passengers_outlier_df = pd.read_csv(\"air_passengers.csv\")\n",
    "air_passengers_outlier_df.columns = [\"time\", \"value\"]\n",
    "\n",
    "# manually add outlier on the date of '1950-12-01'\n",
    "air_passengers_outlier_df.loc[air_passengers_outlier_df.time == '1950-12-01','value']*=5\n",
    "# manually add outlier on the date of '1959-12-01'\n",
    "air_passengers_outlier_df.loc[air_passengers_outlier_df.time == '1959-12-01', 'value']*=4\n",
    "\n",
    "# transform the outlier data into `TimeSeriesData` Object\n",
    "air_passengers_outlier_ts = TimeSeriesData(air_passengers_outlier_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can import and call `OutlierDetector` on `air_passengers_outlier_ts`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from kats.detectors.outlier import OutlierDetector\n",
    "\n",
    "ts_outlierDetection = OutlierDetector(air_passengers_outlier_ts, 'additive') # call OutlierDetector\n",
    "ts_outlierDetection.detector() # apply OutlierDetector"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we look at the outliers that the algorithum found."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Timestamp('1950-12-01 00:00:00'),\n",
       " Timestamp('1959-11-01 00:00:00'),\n",
       " Timestamp('1959-12-01 00:00:00'),\n",
       " Timestamp('1960-11-01 00:00:00'),\n",
       " Timestamp('1960-12-01 00:00:00')]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts_outlierDetection.outliers[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After detecting the outlier, we can now easily removal them from the data. Here we will explore two options: \n",
    "- **No Interpolation**: outlier data points will be replaced with **NaN** values\n",
    "- **With Interpolation**: outlier data points will be replaced with **linear interploation** values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "air_passengers_ts_outliers_removed = ts_outlierDetection.remover(interpolate = False) # No interpolation\n",
    "air_passengers_ts_outliers_interpolated = ts_outlierDetection.remover(interpolate = True) # With interpolation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we visualize the difference between these two approaches to removing outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(20,8), nrows=1, ncols=2)\n",
    "\n",
    "air_passengers_ts_outliers_removed.to_dataframe().plot(x = 'time',y = 'y_0', ax= ax[0])\n",
    "ax[0].set_title(\"Outliers Removed : No interpolation\")\n",
    "air_passengers_ts_outliers_interpolated.to_dataframe().plot(x = 'time',y = 'y_0', ax= ax[1])\n",
    "ax[1].set_title(\"Outliers Removed : With interpolation\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **2.2 MultivariateAnomalyDetector**\n",
    "This anomaly detection method is useful to detect anomalies across multiple time series. Anomalies are detected based on deviations from the predicted steady state behavior. The steady state behavior of a system of metrics is predicted by modeling the linear interdependencies between time series using a Vector Autoregression (VAR) model. \n",
    "\n",
    "This approach is especially suited for detecting multivariate anomalies - small anomalies but persistent across a multiple time series.\n",
    "\n",
    "In addition to identifying an anomalous event, this method has useful utilities to flag specific time series that were affected for a high level root cause analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here are the attributes when initializing `MultivariateAnomalyDetector`:\n",
    "* **data**: TimeSeriesData - Note that data should be deseasonalized and detrended prior to detection\n",
    "* **params**: `VARParams` class initiated with appropriate parameters for the VAR model training\n",
    "* **training_days**: Initial number of days (can be a fraction) to use for training the model. \n",
    "\n",
    "Here are the attributes for the `VARParams` class:\n",
    "* **maxlags**: Maximum number of lags to check for order selection (defaults is 12)\n",
    "* **method**: Estimation method to use (defaults is ordinary least squares (OLS))\n",
    "* **ic**: Information criterion to use for VAR order selection (defaults to None)\n",
    "* **trend**: \n",
    "    * 'c' - add constant (Default), \n",
    "    * 'ct' - constant and trend, \n",
    "    * 'ctt' - constant, linear and quadratic trend,  \n",
    "    * 'n'/'nc' - no constant, no trend"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we provide an example of how to use `MultivariateAnomalyDetector` that uses the `multivariate_anomaly_simulated_data` data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from kats.detectors.outlier import MultivariateAnomalyDetector, MultivariateAnomalyDetectorType\n",
    "from kats.models.var import VARParams\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(action='ignore',category=FutureWarning)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We begin by loading and plotting the data as follows.  We can see that at the end of January, there a subsequent movement in metrics 5 and 6 that represents a multivariate anomaly because of the apparent coordination and persistence of these spikes (even though neither spike is particularly large in magnitude)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load the demo data into a TimeSeriesData Object\n",
    "try: # If running on Jupyter\n",
    "    multi_anomaly_df = pd.read_csv(\"../kats/data/multivariate_anomaly_simulated_data.csv\")\n",
    "except FileNotFoundError: # If running on colab\n",
    "    multi_anomaly_df = pd.read_csv(\"multivariate_anomaly_simulated_data.csv\")\n",
    "multi_anomaly_ts = TimeSeriesData(multi_anomaly_df)\n",
    "\n",
    "# Plot the data\n",
    "multi_anomaly_ts.plot(cols=multi_anomaly_ts.value.columns.tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we train the `MultivariateAnomalyDetector` and plot the results, the first plot gives the time series we previewed above and the second plot gives the overall anomaly scores for the time series.  Since we are using 60 days for training in this example, the first 60 days are not included in the plots below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<AxesSubplot:title={'center':'Input time series metrics'}>,\n",
       "       <AxesSubplot:title={'center':'Overall Anomaly Score'}>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1152 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(10)\n",
    "params = VARParams(maxlags=2)\n",
    "d = MultivariateAnomalyDetector(multi_anomaly_ts, params, training_days=60)\n",
    "anomaly_score_df = d.detector()\n",
    "d.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see above, the overall anomaly score spikes around the end of January.  We can list the specific dates that are anomalies using the `get_anomaly_timepoints` function and specifying the desired significance level (here we use 5%)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Timestamp('2020-01-23 00:00:00'),\n",
       " Timestamp('2020-01-24 00:00:00'),\n",
       " Timestamp('2020-01-25 00:00:00'),\n",
       " Timestamp('2020-01-26 00:00:00'),\n",
       " Timestamp('2020-01-27 00:00:00'),\n",
       " Timestamp('2020-01-28 00:00:00')]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "anomalies = d.get_anomaly_timepoints(alpha=0.05)\n",
    "anomalies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then using the `get_anomalous_metrics` function we can look at the at the top metrics that are contributing to a multivariate anomaly.  In the case of the anomaly times we found here, we can verify that the largest anomaly scores come from metrics 5 and 6."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>metric</th>\n",
       "      <th>anomaly_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5</td>\n",
       "      <td>12.757618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>9.249919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>2.511899</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  metric  anomaly_score\n",
       "0      5      12.757618\n",
       "1      6       9.249919\n",
       "2      4       2.511899"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.get_anomalous_metrics(anomalies[0], top_k=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Trend detection\n",
    "Trend detection tries to identify significant and prolonged changes in a time series.  Rather than identifying change points, trend detection identifies windows of gradual and prolonged change.\n",
    "\n",
    "`MKDetector` is the trend detection algorithm that we include in Kats, which is based on the non-parametric Mann-Kendall (MK) Test.  What the `MKDetector` essentially does is apply a MK to a window of fied size (specified by the `window_size` argument in the `detector` method) and return the end point of each window for which this test is statistically significant.  Trend windows are detected based on the monotonicity of the increases or decreases in the time series in the window, not the magnitude of the change in the value of the time series over the window.  \n",
    "\n",
    "The test statistic for the MK test is called the Kendall's Tau Coefficient, which ranges from -1 to 1.  \n",
    "* A Tau coefficient of -1 indicates a perfectly monotonic decline\n",
    "* A Tau coefficient of 1 indicates a perfectly monotonic increase\n",
    "* A coefficient of 0 indicates there is no directional trend\n",
    "\n",
    "The MK Test converts the Tau Coefficient (along with the value of `window_size`) to a p-value, and we return change points for which the p-value is smaller than `alpha` (0.05 by default).  For additional control of the intensity of the trends we return, we can use the `threshold` attribute in `MKDetector` to put an absolute lower-bound threshold on the value of the Tau Coeffficients for trend windows that are returned. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "These are the parameters to use when initializing `MKDetector`:\n",
    "* **data**: TimeSeriesData, this is time series data at one-day granularity. This time series can be either univariate or multivariate. We require more than training_days points in each time series.\n",
    "* **threshold**: float, threshold for trend intensity; higher threshold gives trend with high intensity (0.8 by default)\n",
    "* **alpha**: float, significance level (0.05 by default)\n",
    "\n",
    "The full set of parameters for the `detector` method in `MKDetector`, all of which are optional and have default values, are as follows: \n",
    "* **window_size**: int, the number of look back days for checking trend persistence (20 days by default)\n",
    "* **training_days**: int, the number of days for time series smoothing; should be greater or equal to window_size (None by default). If training_days is None, we will perform trend detection on the whole time series; otherwise, we will perform trend detection only for the anchor point using the previous training_days data.\n",
    "\n",
    "* **direction**: string, the direction of the trend to be detected, choose from {\"down\", \"up\", \"both\"}  (\"both\" by default)\n",
    "\n",
    "* **freq**: str, the type of seasonality shown in the time series, choose from {'weekly','monthly','yearly'} (None by default)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Basic Usage"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We begin by simulating some data with weekly seasonality using the `Simulator` class.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kats.utils.simulator import Simulator\n",
    "\n",
    "sim = Simulator(n=365, start='2020-01-01', freq='D')\n",
    "tsd = sim.trend_shift_sim(noise=200, seasonal_period=7, seasonal_magnitude=0.007,\n",
    "                              cp_arr=[250], intercept = 10000, trend_arr=[40,-20])\n",
    "\n",
    "# plot the simulated data\n",
    "tsd.plot(cols=['value'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can use the `MKDetector` detector to look for a downward trend.  Because the input data has weekly seasonality, will want to smooth the time series using a 7-day rolling average prior to running the detection algorithm.  We can do this by `freq = 'weekly'` in the `detector` method. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from kats.detectors.trend_mk import MKDetector\n",
    "\n",
    "detector = MKDetector(data=tsd, threshold=.8)\n",
    "# run detector\n",
    "detected_time_points = detector.detector(direction='down', window_size=20, freq='weekly')\n",
    "# plot the results\n",
    "detector.plot(detected_time_points)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interpret the results\n",
    "The return type of the `detector` method is `List[MKChangePoint]`.  Each `MKChangePoint` returned is the end of an increasing or decreasing trend window of duration `window_size`.  In our example, we are looking for decreasing trend windows of length 20."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MKChangePoint(start_time: 2020-10-03 00:00:00, end_time: 2020-10-03 00:00:00, confidence: 0.9999998244557637, detector_type: <class 'kats.detectors.trend_mk.MKDetector'>, is_multivariate: False, trend_direction: decreasing Tau: -0.8526315789473684)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp = detected_time_points[0]\n",
    "cp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The attributes of `MKChangePoint` beyond those of `TimeSeriesChangePoint` are:\n",
    "* **detector_type:** Always `kats.detectors.trend_mk.MKDetector`     \n",
    "* **is_multivariate:** Whether this is a change point for a multivariate time seires\n",
    "* **trend_direction:** Direction of the trend, either 'increasing' or 'decreasing'\n",
    "* **Tau:** kendall's Tau value for the change point.  This is a float for univariate time series and a dictionary for multivariate time series"
   ]
  }
 ],
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